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Well I guess computing in astrophysics and HEP isn't that interesting then :) It's true that we need shared data, but we don't need shared state (memory) for a
by batbomb 10y ago
Well I guess computing in astrophysics and HEP isn't that interesting then :)
It's true that we need shared data, but we don't need shared state (memory) for any of our workloads, and shared data (e.g. disk/db) is a much easier problem to solve than shared state.
There is still coordination and orchestration, but that's an extremely coarse amount of communication compared to the cost of Cray interconnects. That being said, there are cases where we might benefit from the Cray networking, but that comes at the cost of other tradeoffs (no local disk, low memory per core).
So what do we do? Well, we use a handful of Ferraris to get the job done because they are available when cheap bus would have suited us fine. The double whammy is that the Ferraris end up in the shop all the time and occasionally somebody else gets exclusivity to them when they want to get in a Bell prize submission.
- cinquemb 10y agoWell this is where you talk to the network admins at your university and get them in on a top secret program, code name: "It Was China", to hack into all the detectable ps4's on campus, call all those students to a hall for a random lottery social for a couple of hours while you commandeer there equipment, for science of course. Or you can send get the network admins to allow you to send them a email, but the first suggestion sounds more fun :P
- nickbauman 10y agoThat, sir, is hilariously awesome.
- nickbauman 10y agoWell here are two examples. 1) I have a rail system that I want to optimize train movement through the topology. My search space is the number of running locomotives to the power of the number of switches in the system. On a continental rail system, that's a number with many, many, many zeros after it. To optimize this, I have many cores chewing through the space, but to know where to search they must share a visited node cache otherwise they will search each others space and waste effort. 2) I have a system that predicts part failures by collecting sensor data of the machine in a time series. I must look for patterns of change in these sensor readings and compare that to patterns that I know about, often drilling through data over many weeks looking for feature alignment in the sensor matrices. Same problem: many cores, some amount of space that is known vs. unknown that must be shared, but as a result is a contentious resource.